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<div class="title">mls.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * Copyright (c) 2009-2011, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * All rights reserved.</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * are met:</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *   notice, this list of conditions and the following disclaimer.</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * * Redistributions in binary form must reproduce the above</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> *   copyright notice, this list of conditions and the following</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> *   disclaimer in the documentation and/or other materials provided</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> *   with the distribution.</span></div>
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<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> *   contributors may be used to endorse or promote products derived</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> *   from this software without specific prior written permission.</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="comment"> * &quot;AS IS&quot; AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT</span></div>
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<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="comment"> * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER</span></div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="comment"> * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT</span></div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="comment"> * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN</span></div>
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<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="comment"> * POSSIBILITY OF SUCH DAMAGE.</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="comment"> * $Id$</span></div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160; </div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="preprocessor">#ifndef PCL_SURFACE_IMPL_MLS_H_</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#define PCL_SURFACE_IMPL_MLS_H_</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160; </div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &lt;pcl/point_traits.h&gt;</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#include &lt;pcl/surface/mls.h&gt;</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#include &lt;pcl/common/io.h&gt;</span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#include &lt;pcl/common/copy_point.h&gt;</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="centroid_8h.html">pcl/common/centroid.h</a>&gt;</span></div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="preprocessor">#include &lt;pcl/common/eigen.h&gt;</span></div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="common_2include_2pcl_2common_2geometry_8h.html">pcl/common/geometry.h</a>&gt;</span></div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160; </div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="preprocessor">#include &lt;omp.h&gt;</span></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160; </div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classpcl_1_1_moving_least_squares.html#ad168be16626ea58d1c31c321bd1d980f">   57</a></span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html#ad168be16626ea58d1c31c321bd1d980f">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::process</a> (<a class="code" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;output)</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;{</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <span class="comment">// Reset or initialize the collection of indices</span></div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  corresponding_input_indices_.reset (<span class="keyword">new</span> <a class="code" href="structpcl_1_1_point_indices.html">PointIndices</a>);</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160; </div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  <span class="comment">// Check if normals have to be computed/saved</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;  {</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    normals_.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">NormalCloud</a>);</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="comment">// Copy the header</span></div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    normals_-&gt;header = input_-&gt;header;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <span class="comment">// Clear the fields in case the method exits before computation</span></div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    normals_-&gt;width = normals_-&gt;height = 0;</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    normals_-&gt;points.clear ();</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  }</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160; </div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160; </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <span class="comment">// Copy the header</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  output.<a class="code" href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">header</a> = input_-&gt;header;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;  output.<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a> = output.<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a> = 0;</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  output.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.clear ();</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160; </div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keywordflow">if</span> (search_radius_ &lt;= 0 || sqr_gauss_param_ &lt;= 0)</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  {</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::process] Invalid search radius (%f) or Gaussian parameter (%f)!\n&quot;</span>, getClassName ().c_str (), search_radius_, sqr_gauss_param_);</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  }</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160; </div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  <span class="comment">// Check if distinct_cloud_ was set</span></div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  <span class="keywordflow">if</span> (upsample_method_ == DISTINCT_CLOUD &amp;&amp; !distinct_cloud_)</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  {</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::process] Upsample method was set to DISTINCT_CLOUD, but no distinct cloud was specified.\n&quot;</span>, getClassName ().c_str ());</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  }</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  <span class="keywordflow">if</span> (!initCompute ())</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160; </div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  <span class="comment">// Initialize the spatial locator</span></div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  <span class="keywordflow">if</span> (!tree_)</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;  {</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    KdTreePtr tree;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    <span class="keywordflow">if</span> (input_-&gt;isOrganized ())</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;      tree.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1search_1_1_organized_neighbor.html">pcl::search::OrganizedNeighbor&lt;PointInT&gt;</a> ());</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      tree.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree&lt;PointInT&gt;</a> (<span class="keyword">false</span>));</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    setSearchMethod (tree);</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;  }</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160; </div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  <span class="comment">// Send the surface dataset to the spatial locator</span></div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;  tree_-&gt;setInputCloud (input_);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160; </div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  <span class="keywordflow">switch</span> (upsample_method_)</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  {</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="comment">// Initialize random number generator if necessary</span></div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    <span class="keywordflow">case</span> (RANDOM_UNIFORM_DENSITY):</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      rng_alg_.seed (<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span><span class="keyword">&gt;</span> (std::time (0)));</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      <span class="keywordtype">float</span> tmp = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (search_radius_ / 2.0f);</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      boost::uniform_real&lt;float&gt; uniform_distrib (-tmp, tmp);</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;      rng_uniform_distribution_.reset (<span class="keyword">new</span> boost::variate_generator&lt;boost::mt19937&amp;, boost::uniform_real&lt;float&gt; &gt; (rng_alg_, uniform_distrib));</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160; </div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;      mls_results_.resize (1); <span class="comment">// Need to have a reference to a single dummy result.</span></div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      </div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    }</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    <span class="keywordflow">case</span> (VOXEL_GRID_DILATION):</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <span class="keywordflow">case</span> (DISTINCT_CLOUD):</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;      {</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        mls_results_.resize (input_-&gt;size ());</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;      }</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      {</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;        mls_results_.resize (1); <span class="comment">// Need to have a reference to a single dummy result.</span></div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;      }</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  }</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160; </div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  <span class="comment">// Perform the actual surface reconstruction</span></div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  performProcessing (output);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  {</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    normals_-&gt;height = 1;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    normals_-&gt;width = <span class="keyword">static_cast&lt;</span>uint32_t<span class="keyword">&gt;</span> (normals_-&gt;size ());</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160; </div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; output.size (); ++i)</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    {</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;      <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structpcl_1_1traits_1_1field_list.html">pcl::traits::fieldList&lt;PointOutT&gt;::type</a> FieldList;</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;      pcl::for_each_type&lt;FieldList&gt; (<a class="code" href="structpcl_1_1_set_if_field_exists.html">SetIfFieldExists&lt;PointOutT, float&gt;</a> (output.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i], <span class="stringliteral">&quot;normal_x&quot;</span>, normals_-&gt;points[i].normal_x));</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;      pcl::for_each_type&lt;FieldList&gt; (<a class="code" href="structpcl_1_1_set_if_field_exists.html">SetIfFieldExists&lt;PointOutT, float&gt;</a> (output.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i], <span class="stringliteral">&quot;normal_y&quot;</span>, normals_-&gt;points[i].normal_y));</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;      pcl::for_each_type&lt;FieldList&gt; (<a class="code" href="structpcl_1_1_set_if_field_exists.html">SetIfFieldExists&lt;PointOutT, float&gt;</a> (output.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i], <span class="stringliteral">&quot;normal_z&quot;</span>, normals_-&gt;points[i].normal_z));</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;      pcl::for_each_type&lt;FieldList&gt; (<a class="code" href="structpcl_1_1_set_if_field_exists.html">SetIfFieldExists&lt;PointOutT, float&gt;</a> (output.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i], <span class="stringliteral">&quot;curvature&quot;</span>, normals_-&gt;points[i].curvature));</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    }</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160; </div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;  }</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160; </div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;  <span class="comment">// Set proper widths and heights for the clouds</span></div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  output.<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a> = 1;</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;  output.<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a> = <span class="keyword">static_cast&lt;</span>uint32_t<span class="keyword">&gt;</span> (output.size ());</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160; </div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  deinitCompute ();</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;}</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160; </div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00165"></a><span class="lineno"><a class="line" href="classpcl_1_1_moving_least_squares.html#af89da1f47e32a533e5c0c75d1a244a74">  165</a></span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html#af89da1f47e32a533e5c0c75d1a244a74">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::computeMLSPointNormal</a> (<span class="keywordtype">int</span> index,</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;                                                                     <span class="keyword">const</span> std::vector&lt;int&gt; &amp;nn_indices,</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;                                                                     std::vector&lt;float&gt; &amp;nn_sqr_dists,</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;                                                                     <a class="code" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;projected_points,</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                                                                     <a class="code" href="classpcl_1_1_point_cloud.html">NormalCloud</a> &amp;projected_points_normals,</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;                                                                     <a class="code" href="structpcl_1_1_point_indices.html">PointIndices</a> &amp;corresponding_input_indices,</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;                                                                     <a class="code" href="structpcl_1_1_moving_least_squares_1_1_m_l_s_result.html">MLSResult</a> &amp;mls_result)<span class="keyword"> const</span></div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  <span class="comment">// Note: this method is const because it needs to be thread-safe</span></div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  <span class="comment">//       (MovingLeastSquaresOMP calls it from multiple threads)</span></div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160; </div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;  <span class="comment">// Compute the plane coefficients</span></div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  EIGEN_ALIGN16 Eigen::Matrix3d covariance_matrix;</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;  Eigen::Vector4d xyz_centroid;</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  <span class="comment">// Estimate the XYZ centroid</span></div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a> (*input_, nn_indices, xyz_centroid);</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160; </div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;  <span class="comment">// Compute the 3x3 covariance matrix</span></div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">pcl::computeCovarianceMatrix</a> (*input_, nn_indices, xyz_centroid, covariance_matrix);</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  EIGEN_ALIGN16 Eigen::Vector3d::Scalar eigen_value;</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;  EIGEN_ALIGN16 Eigen::Vector3d eigen_vector;</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  Eigen::Vector4d model_coefficients;</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  <a class="code" href="group__common.html#gaca873868052e7d26efcf4b684a17bef2">pcl::eigen33</a> (covariance_matrix, eigen_value, eigen_vector);</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;  model_coefficients.head&lt;3&gt; ().matrix () = eigen_vector;</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  model_coefficients[3] = 0;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;  model_coefficients[3] = -1 * model_coefficients.dot (xyz_centroid);</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160; </div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  <span class="comment">// Projected query point</span></div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  Eigen::Vector3d point = input_-&gt;points[index].getVector3fMap ().template cast&lt;double&gt; ();</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;  <span class="keywordtype">double</span> distance = point.dot (model_coefficients.head&lt;3&gt; ()) + model_coefficients[3];</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  point -= distance * model_coefficients.head&lt;3&gt; ();</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160; </div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  <span class="keywordtype">float</span> curvature = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (covariance_matrix.trace ());</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;  <span class="comment">// Compute the curvature surface change</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;  <span class="keywordflow">if</span> (curvature != 0)</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    curvature = fabsf (<span class="keywordtype">float</span> (eigen_value / <span class="keywordtype">double</span> (curvature)));</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160; </div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160; </div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;  <span class="comment">// Get a copy of the plane normal easy access</span></div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;  Eigen::Vector3d plane_normal = model_coefficients.head&lt;3&gt; ();</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;  <span class="comment">// Vector in which the polynomial coefficients will be put</span></div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;  Eigen::VectorXd c_vec;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;  <span class="comment">// Local coordinate system (Darboux frame)</span></div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;  Eigen::Vector3d v_axis (0.0f, 0.0f, 0.0f), u_axis (0.0f, 0.0f, 0.0f);</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160; </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;  <span class="comment">// Perform polynomial fit to update point and normal</span></div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;<span class="comment"></span>  <span class="keywordflow">if</span> (polynomial_fit_ &amp;&amp; <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (nn_indices.size ()) &gt;= nr_coeff_)</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;  {</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    <span class="comment">// Update neighborhood, since point was projected, and computing relative</span></div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    <span class="comment">// positions. Note updating only distances for the weights for speed</span></div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    std::vector&lt;Eigen::Vector3d, Eigen::aligned_allocator&lt;Eigen::Vector3d&gt; &gt; de_meaned (nn_indices.size ());</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> ni = 0; ni &lt; nn_indices.size (); ++ni)</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    {</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;      de_meaned[ni][0] = input_-&gt;points[nn_indices[ni]].x - point[0];</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;      de_meaned[ni][1] = input_-&gt;points[nn_indices[ni]].y - point[1];</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;      de_meaned[ni][2] = input_-&gt;points[nn_indices[ni]].z - point[2];</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;      nn_sqr_dists[ni] = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (de_meaned[ni].dot (de_meaned[ni]));</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    }</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160; </div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    <span class="comment">// Allocate matrices and vectors to hold the data used for the polynomial fit</span></div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    Eigen::VectorXd weight_vec (nn_indices.size ());</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    Eigen::MatrixXd P (nr_coeff_, nn_indices.size ());</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    Eigen::VectorXd f_vec (nn_indices.size ());</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    Eigen::MatrixXd P_weight; <span class="comment">// size will be (nr_coeff_, nn_indices.size ());</span></div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    Eigen::MatrixXd P_weight_Pt (nr_coeff_, nr_coeff_);</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160; </div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    <span class="comment">// Get local coordinate system (Darboux frame)</span></div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    v_axis = plane_normal.unitOrthogonal ();</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;    u_axis = plane_normal.cross (v_axis);</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160; </div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    <span class="comment">// Go through neighbors, transform them in the local coordinate system,</span></div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;    <span class="comment">// save height and the evaluation of the polynome&#39;s terms</span></div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="keywordtype">double</span> u_coord, v_coord, u_pow, v_pow;</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> ni = 0; ni &lt; nn_indices.size (); ++ni)</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    {</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;      <span class="comment">// (Re-)compute weights</span></div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;      weight_vec (ni) = exp (-nn_sqr_dists[ni] / sqr_gauss_param_);</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160; </div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      <span class="comment">// Transforming coordinates</span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      u_coord = de_meaned[ni].dot (u_axis);</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;      v_coord = de_meaned[ni].dot (v_axis);</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;      f_vec (ni) = de_meaned[ni].dot (plane_normal);</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160; </div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;      <span class="comment">// Compute the polynomial&#39;s terms at the current point</span></div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;      <span class="keywordtype">int</span> j = 0;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;      u_pow = 1;</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> ui = 0; ui &lt;= order_; ++ui)</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;      {</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;        v_pow = 1;</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> vi = 0; vi &lt;= order_ - ui; ++vi)</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;        {</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;          P (j++, ni) = u_pow * v_pow;</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;          v_pow *= v_coord;</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;        }</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        u_pow *= u_coord;</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;      }</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;    }</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160; </div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;    <span class="comment">// Computing coefficients</span></div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    P_weight = P * weight_vec.asDiagonal ();</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    P_weight_Pt = P_weight * P.transpose ();</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    c_vec = P_weight * f_vec;</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    P_weight_Pt.llt ().solveInPlace (c_vec);</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;  }</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160; </div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;  <span class="keywordflow">switch</span> (upsample_method_)</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;  {</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    <span class="keywordflow">case</span> (NONE):</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    {</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;      Eigen::Vector3d normal = plane_normal;</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160; </div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;      <span class="keywordflow">if</span> (polynomial_fit_ &amp;&amp; <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (nn_indices.size ()) &gt;= nr_coeff_ &amp;&amp; pcl_isfinite (c_vec[0]))</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;      {</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        point += (c_vec[0] * plane_normal);</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160; </div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;        <span class="comment">// Compute tangent vectors using the partial derivates evaluated at (0,0) which is c_vec[order_+1] and c_vec[1]</span></div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;        <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;          normal = plane_normal - c_vec[order_ + 1] * u_axis - c_vec[1] * v_axis;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;      }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160; </div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;      PointOutT aux;</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;      aux.x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (point[0]);</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;      aux.y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (point[1]);</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;      aux.z = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (point[2]);</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (aux);</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160; </div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;      <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;      {</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;        <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> aux_normal;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;        aux_normal.normal_x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[0]);</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;        aux_normal.normal_y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[1]);</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        aux_normal.normal_z = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[2]);</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        aux_normal.curvature = curvature;</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        projected_points_normals.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (aux_normal);</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;        corresponding_input_indices.indices.push_back (index);</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;      }</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160; </div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    }</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160; </div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    <span class="keywordflow">case</span> (SAMPLE_LOCAL_PLANE):</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    {</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;      <span class="comment">// Uniformly sample a circle around the query point using the radius and step parameters</span></div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">float</span> u_disp = -<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (upsampling_radius_); u_disp &lt;= upsampling_radius_; u_disp += static_cast&lt;float&gt; (upsampling_step_))</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">float</span> v_disp = -<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (upsampling_radius_); v_disp &lt;= upsampling_radius_; v_disp += static_cast&lt;float&gt; (upsampling_step_))</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;          <span class="keywordflow">if</span> (u_disp*u_disp + v_disp*v_disp &lt; upsampling_radius_*upsampling_radius_)</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;          {</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;            PointOutT projected_point;</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;            <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> projected_normal;</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;            projectPointToMLSSurface (u_disp, v_disp, u_axis, v_axis, plane_normal, point,</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;                                      curvature, c_vec,</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;                                      <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (nn_indices.size ()),</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;                                      projected_point, projected_normal);</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160; </div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;            projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (projected_point);</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;            corresponding_input_indices.indices.push_back (index);</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;            <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;              projected_points_normals.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (projected_normal);</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;          }</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    }</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160; </div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    <span class="keywordflow">case</span> (RANDOM_UNIFORM_DENSITY):</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    {</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;      <span class="comment">// Compute the local point density and add more samples if necessary</span></div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;      <span class="keywordtype">int</span> num_points_to_add = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (floor (desired_num_points_in_radius_ / 2.0 / <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (nn_indices.size ())));</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160; </div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;      <span class="comment">// Just add the query point, because the density is good</span></div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;      <span class="keywordflow">if</span> (num_points_to_add &lt;= 0)</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;      {</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;        <span class="comment">// Just add the current point</span></div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;        Eigen::Vector3d normal = plane_normal;</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;        <span class="keywordflow">if</span> (polynomial_fit_ &amp;&amp; <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (nn_indices.size ()) &gt;= nr_coeff_ &amp;&amp; pcl_isfinite (c_vec[0]))</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;        {</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;          <span class="comment">// Projection onto MLS surface along Darboux normal to the height at (0,0)</span></div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;          point += (c_vec[0] * plane_normal);</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;          <span class="comment">// Compute tangent vectors using the partial derivates evaluated at (0,0) which is c_vec[order_+1] and c_vec[1]</span></div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;          <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;            normal = plane_normal - c_vec[order_ + 1] * u_axis - c_vec[1] * v_axis;</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;        }</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;        PointOutT aux;</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;        aux.x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (point[0]);</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;        aux.y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (point[1]);</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;        aux.z = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (point[2]);</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;        projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (aux);</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;        corresponding_input_indices.indices.push_back (index);</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160; </div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;        <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;        {</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;          <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> aux_normal;</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;          aux_normal.normal_x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[0]);</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;          aux_normal.normal_y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[1]);</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;          aux_normal.normal_z = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[2]);</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;          aux_normal.curvature = curvature;</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;          projected_points_normals.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (aux_normal);</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;        }</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;      }</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;      <span class="keywordflow">else</span></div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;      {</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;        <span class="comment">// Sample the local plane</span></div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> num_added = 0; num_added &lt; num_points_to_add;)</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;        {</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;          <span class="keywordtype">float</span> u_disp = (*rng_uniform_distribution_) (),</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;              v_disp = (*rng_uniform_distribution_) ();</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;          <span class="comment">// Check if inside circle; if not, try another coin flip</span></div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;          <span class="keywordflow">if</span> (u_disp * u_disp + v_disp * v_disp &gt; search_radius_ * search_radius_/4)</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;            <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160; </div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160; </div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;          PointOutT projected_point;</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;          <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> projected_normal;</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;          projectPointToMLSSurface (u_disp, v_disp, u_axis, v_axis, plane_normal, point,</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;                                    curvature, c_vec,</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;                                    <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (nn_indices.size ()),</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;                                    projected_point, projected_normal);</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160; </div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;          projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (projected_point);</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;          corresponding_input_indices.indices.push_back (index);</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;          <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;            projected_points_normals.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (projected_normal);</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160; </div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;          num_added ++;</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;        }</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;      }</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;    }</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160; </div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;    <span class="keywordflow">case</span> (VOXEL_GRID_DILATION):</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;    <span class="keywordflow">case</span> (DISTINCT_CLOUD):</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;    {</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;      <span class="comment">// Take all point pairs and sample space between them in a grid-fashion</span></div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;      <span class="comment">// \note consider only point pairs with increasing indices</span></div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;      mls_result = <a class="code" href="structpcl_1_1_moving_least_squares_1_1_m_l_s_result.html">MLSResult</a> (point, plane_normal, u_axis, v_axis, c_vec, <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (nn_indices.size ()), curvature);</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;    }</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;  }</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;}</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160; </div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00409"></a><span class="lineno"><a class="line" href="classpcl_1_1_moving_least_squares.html#a0e2f25248f7f01a111763877698e06e4">  409</a></span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html#a0e2f25248f7f01a111763877698e06e4">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::projectPointToMLSSurface</a> (<span class="keywordtype">float</span> &amp;u_disp, <span class="keywordtype">float</span> &amp;v_disp,</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;                                                                        Eigen::Vector3d &amp;u, Eigen::Vector3d &amp;v,</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;                                                                        Eigen::Vector3d &amp;plane_normal,</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;                                                                        Eigen::Vector3d &amp;mean,</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;                                                                        <span class="keywordtype">float</span> &amp;curvature,</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;                                                                        Eigen::VectorXd &amp;c_vec,</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;                                                                        <span class="keywordtype">int</span> num_neighbors,</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;                                                                        PointOutT &amp;result_point,</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;                                                                        <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> &amp;result_normal)<span class="keyword"> const</span></div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;  <span class="keywordtype">double</span> n_disp = 0.0f;</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;  <span class="keywordtype">double</span> d_u = 0.0f, d_v = 0.0f;</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160; </div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;  <span class="comment">// HARDCODED 5*nr_coeff_ to guarantee that the computed polynomial had a proper point set basis</span></div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;  <span class="keywordflow">if</span> (polynomial_fit_ &amp;&amp; num_neighbors &gt;= 5*nr_coeff_ &amp;&amp; pcl_isfinite (c_vec[0]))</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;  {</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    <span class="comment">// Compute the displacement along the normal using the fitted polynomial</span></div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;    <span class="comment">// and compute the partial derivatives needed for estimating the normal</span></div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;    <span class="keywordtype">int</span> j = 0;</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;    <span class="keywordtype">float</span> u_pow = 1.0f, v_pow = 1.0f, u_pow_prev = 1.0f, v_pow_prev = 1.0f;</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> ui = 0; ui &lt;= order_; ++ui)</div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;    {</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;      v_pow = 1;</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> vi = 0; vi &lt;= order_ - ui; ++vi)</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;      {</div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;        <span class="comment">// Compute displacement along normal</span></div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;        n_disp += u_pow * v_pow * c_vec[j++];</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160; </div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;        <span class="comment">// Compute partial derivatives</span></div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;        <span class="keywordflow">if</span> (ui &gt;= 1)</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;          d_u += c_vec[j-1] * ui * u_pow_prev * v_pow;</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;        <span class="keywordflow">if</span> (vi &gt;= 1)</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;          d_v += c_vec[j-1] * vi * u_pow * v_pow_prev;</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160; </div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;        v_pow_prev = v_pow;</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;        v_pow *= v_disp;</div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;      }</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;      u_pow_prev = u_pow;</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;      u_pow *= u_disp;</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    }</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;  }</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160; </div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;  result_point.x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (mean[0] + u[0] * u_disp + v[0] * v_disp + plane_normal[0] * n_disp);</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;  result_point.y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (mean[1] + u[1] * u_disp + v[1] * v_disp + plane_normal[1] * n_disp);</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;  result_point.z = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (mean[2] + u[2] * u_disp + v[2] * v_disp + plane_normal[2] * n_disp);</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160; </div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;  Eigen::Vector3d normal = plane_normal - d_u * u - d_v * v;</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;  normal.normalize ();</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160; </div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;  result_normal.normal_x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[0]);</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;  result_normal.normal_y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[1]);</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;  result_normal.normal_z = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (normal[2]);</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;  result_normal.curvature = curvature;</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;}</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160; </div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00466"></a><span class="lineno"><a class="line" href="classpcl_1_1_moving_least_squares.html#ae27440d95b1fc5568b2ec820302654a4">  466</a></span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html#ae27440d95b1fc5568b2ec820302654a4">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::performProcessing</a> (<a class="code" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;output)</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;{</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;  <span class="comment">// Compute the number of coefficients</span></div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;  nr_coeff_ = (order_ + 1) * (order_ + 2) / 2;</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160; </div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;  <span class="comment">// Allocate enough space to hold the results of nearest neighbor searches</span></div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;  <span class="comment">// \note resize is irrelevant for a radiusSearch ().</span></div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;  std::vector&lt;int&gt; nn_indices;</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;  std::vector&lt;float&gt; nn_sqr_dists;</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;  </div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;  <span class="keywordtype">size_t</span> mls_result_index = 0;</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160; </div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;  <span class="comment">// For all points</span></div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> cp = 0; cp &lt; indices_-&gt;size (); ++cp)</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  {</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;    <span class="comment">// Get the initial estimates of point positions and their neighborhoods</span></div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;    <span class="keywordflow">if</span> (!searchForNeighbors ((*indices_)[cp], nn_indices, nn_sqr_dists))</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160; </div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160; </div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;    <span class="comment">// Check the number of nearest neighbors for normal estimation (and later</span></div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;    <span class="comment">// for polynomial fit as well)</span></div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;    <span class="keywordflow">if</span> (nn_indices.size () &lt; 3)</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160; </div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160; </div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    <a class="code" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> projected_points;</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;    <a class="code" href="classpcl_1_1_point_cloud.html">NormalCloud</a> projected_points_normals;</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;    <span class="comment">// Get a plane approximating the local surface&#39;s tangent and project point onto it</span></div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;    <span class="keywordtype">int</span> index = (*indices_)[cp];</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;    </div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;    <span class="keywordflow">if</span> (upsample_method_ == VOXEL_GRID_DILATION || upsample_method_ == DISTINCT_CLOUD)</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;      mls_result_index = index; <span class="comment">// otherwise we give it a dummy location.</span></div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160; </div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    computeMLSPointNormal (index, nn_indices, nn_sqr_dists, projected_points, projected_points_normals, *corresponding_input_indices_, mls_results_[mls_result_index]);</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160; </div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160; </div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;    <span class="comment">// Copy all information from the input cloud to the output points (not doing any interpolation)</span></div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> pp = 0; pp &lt; projected_points.size (); ++pp)</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;      copyMissingFields (input_-&gt;points[(*indices_)[cp]], projected_points[pp]);</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160; </div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160; </div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    <span class="comment">// Append projected points to output</span></div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;    output.<a class="code" href="classpcl_1_1_point_cloud.html#a75387c07a2d24ee943eb71ab1c00e4a7">insert</a> (output.end (), projected_points.begin (), projected_points.end ());</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;    <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;      normals_-&gt;insert (normals_-&gt;end (), projected_points_normals.begin (), projected_points_normals.end ());</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;  }</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160; </div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;  <span class="comment">// Perform the distinct-cloud or voxel-grid upsampling</span></div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;  performUpsampling (output);</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;}</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160; </div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;pcl::MovingLeastSquaresOMP&lt;PointInT, PointOutT&gt;::performProcessing (PointCloudOut &amp;output)</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;{</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;  <span class="comment">// Compute the number of coefficients</span></div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;  nr_coeff_ = (order_ + 1) * (order_ + 2) / 2;</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160; </div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;  <span class="comment">// (Maximum) number of threads</span></div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> threads = threads_ == 0 ? 1 : threads_;</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160; </div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;  <span class="comment">// Create temporaries for each thread in order to avoid synchronization</span></div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;  <span class="keyword">typename</span> PointCloudOut::CloudVectorType projected_points (threads);</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;  <span class="keyword">typename</span> NormalCloud::CloudVectorType projected_points_normals (threads);</div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;  std::vector&lt;PointIndices&gt; corresponding_input_indices (threads);</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160; </div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;  <span class="comment">// For all points</span></div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;<span class="preprocessor">#pragma omp parallel for schedule (dynamic,1000) num_threads (threads)</span></div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> cp = 0; cp &lt; static_cast&lt;int&gt; (indices_-&gt;size ()); ++cp)</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;  {</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;    <span class="comment">// Allocate enough space to hold the results of nearest neighbor searches</span></div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    <span class="comment">// \note resize is irrelevant for a radiusSearch ().</span></div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;    std::vector&lt;int&gt; nn_indices;</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;    std::vector&lt;float&gt; nn_sqr_dists;</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160; </div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;    <span class="comment">// Get the initial estimates of point positions and their neighborhoods</span></div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;    <span class="keywordflow">if</span> (this-&gt;searchForNeighbors ((*indices_)[cp], nn_indices, nn_sqr_dists))</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;    {</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;      <span class="comment">// Check the number of nearest neighbors for normal estimation (and later</span></div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;      <span class="comment">// for polynomial fit as well)</span></div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;      <span class="keywordflow">if</span> (nn_indices.size () &gt;= 3)</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;      {</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;        <span class="comment">// This thread&#39;s ID (range 0 to threads-1)</span></div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;        <span class="keywordtype">int</span> tn = omp_get_thread_num ();</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160; </div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;        <span class="comment">// Size of projected points before computeMLSPointNormal () adds points</span></div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;        <span class="keywordtype">size_t</span> pp_size = projected_points[tn].size ();</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160; </div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;        <span class="comment">// Get a plane approximating the local surface&#39;s tangent and project point onto it</span></div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;        <span class="keywordtype">int</span> index = (*indices_)[cp];</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;        <span class="keywordtype">size_t</span> mls_result_index = 0;</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;        </div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;        <span class="keywordflow">if</span> (upsample_method_ == VOXEL_GRID_DILATION || upsample_method_ == DISTINCT_CLOUD)</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;          mls_result_index = index; <span class="comment">// otherwise we give it a dummy location.</span></div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;        </div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;        this-&gt;computeMLSPointNormal (index, nn_indices, nn_sqr_dists, projected_points[tn], projected_points_normals[tn], corresponding_input_indices[tn], this-&gt;mls_results_[mls_result_index]);</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160; </div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;        <span class="comment">// Copy all information from the input cloud to the output points (not doing any interpolation)</span></div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> pp = pp_size; pp &lt; projected_points[tn].size (); ++pp)</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;          this-&gt;copyMissingFields (input_-&gt;points[(*indices_)[cp]], projected_points[tn][pp]);</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;        }</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;      }</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;  }</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160; </div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160; </div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;  <span class="comment">// Combine all threads&#39; results into the output vectors</span></div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tn = 0; tn &lt; threads; ++tn)</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;  {</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;    output.insert (output.end (), projected_points[tn].begin (), projected_points[tn].end ());</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;    corresponding_input_indices_-&gt;indices.insert (corresponding_input_indices_-&gt;indices.end (),</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;        corresponding_input_indices[tn].indices.begin (), corresponding_input_indices[tn].indices.end ());</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;    <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;      normals_-&gt;insert (normals_-&gt;end (), projected_points_normals[tn].begin (), projected_points_normals[tn].end ());</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;  }</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160; </div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;  <span class="comment">// Perform the distinct-cloud or voxel-grid upsampling</span></div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;  this-&gt;performUpsampling (output);</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;}</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160; </div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00590"></a><span class="lineno"><a class="line" href="classpcl_1_1_moving_least_squares.html#a1a4ffe40c701474aa4f18758d2432ca7">  590</a></span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html#a1a4ffe40c701474aa4f18758d2432ca7">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::performUpsampling</a> (<a class="code" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;output)</div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;{</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;  <span class="keywordflow">if</span> (upsample_method_ == DISTINCT_CLOUD)</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;  {</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> dp_i = 0; dp_i &lt; distinct_cloud_-&gt;size (); ++dp_i) <span class="comment">// dp_i = distinct_point_i</span></div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;    {</div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;      <span class="comment">// Distinct cloud may have nan points, skip them</span></div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;      <span class="keywordflow">if</span> (!pcl_isfinite (distinct_cloud_-&gt;points[dp_i].x))</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160; </div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;      <span class="comment">// Get 3D position of point</span></div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;      <span class="comment">//Eigen::Vector3f pos = distinct_cloud_-&gt;points[dp_i].getVector3fMap ();</span></div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;      std::vector&lt;int&gt; nn_indices;</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;      std::vector&lt;float&gt; nn_dists;</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;      tree_-&gt;nearestKSearch (distinct_cloud_-&gt;points[dp_i], 1, nn_indices, nn_dists);</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;      <span class="keywordtype">int</span> input_index = nn_indices.front ();</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160; </div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;      <span class="comment">// If the closest point did not have a valid MLS fitting result</span></div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;      <span class="comment">// OR if it is too far away from the sampled point</span></div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;      <span class="keywordflow">if</span> (mls_results_[input_index].valid == <span class="keyword">false</span>)</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160; </div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;      Eigen::Vector3d add_point = distinct_cloud_-&gt;points[dp_i].getVector3fMap ().template cast&lt;double&gt; ();</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160; </div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;      <span class="keywordtype">float</span> u_disp = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> ((add_point - mls_results_[input_index].mean).dot (mls_results_[input_index].u_axis)),</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;            v_disp = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> ((add_point - mls_results_[input_index].mean).dot (mls_results_[input_index].v_axis));</div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160; </div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;      PointOutT result_point;</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;      <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> result_normal;</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;      projectPointToMLSSurface (u_disp, v_disp,</div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;                                mls_results_[input_index].u_axis, mls_results_[input_index].v_axis,</div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;                                mls_results_[input_index].plane_normal,</div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;                                mls_results_[input_index].mean,</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;                                mls_results_[input_index].curvature,</div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;                                mls_results_[input_index].c_vec,</div>
<div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160;                                mls_results_[input_index].num_neighbors,</div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;                                result_point, result_normal);</div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160; </div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;      <span class="comment">// Copy additional point information if available</span></div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;      copyMissingFields (input_-&gt;points[input_index], result_point);</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160; </div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;      <span class="comment">// Store the id of the original point</span></div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;      corresponding_input_indices_-&gt;indices.push_back (input_index);</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160; </div>
<div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;      output.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (result_point);</div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;      <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;        normals_-&gt;push_back (result_normal);</div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;    }</div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;  }</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160; </div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;  <span class="comment">// For the voxel grid upsampling method, generate the voxel grid and dilate it</span></div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;  <span class="comment">// Then, project the newly obtained points to the MLS surface</span></div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;  <span class="keywordflow">if</span> (upsample_method_ == VOXEL_GRID_DILATION)</div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;  {</div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;    <a class="code" href="classpcl_1_1_moving_least_squares_1_1_m_l_s_voxel_grid.html">MLSVoxelGrid</a> voxel_grid (input_, indices_, voxel_size_);</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> iteration = 0; iteration &lt; dilation_iteration_num_; ++iteration)</div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;      voxel_grid.dilate ();</div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160; </div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">typename</span> MLSVoxelGrid::HashMap::iterator m_it = voxel_grid.voxel_grid_.begin (); m_it != voxel_grid.voxel_grid_.end (); ++m_it)</div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;    {</div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;      <span class="comment">// Get 3D position of point</span></div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;      Eigen::Vector3f pos;</div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;      voxel_grid.getPosition (m_it-&gt;first, pos);</div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160; </div>
<div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160;      PointInT p;</div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;      p.x = pos[0];</div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;      p.y = pos[1];</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;      p.z = pos[2];</div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160; </div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;      std::vector&lt;int&gt; nn_indices;</div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;      std::vector&lt;float&gt; nn_dists;</div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;      tree_-&gt;nearestKSearch (p, 1, nn_indices, nn_dists);</div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;      <span class="keywordtype">int</span> input_index = nn_indices.front ();</div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160; </div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;      <span class="comment">// If the closest point did not have a valid MLS fitting result</span></div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;      <span class="comment">// OR if it is too far away from the sampled point</span></div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;      <span class="keywordflow">if</span> (mls_results_[input_index].valid == <span class="keyword">false</span>)</div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160; </div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;      Eigen::Vector3d add_point = p.getVector3fMap ().template cast&lt;double&gt; ();</div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;      <span class="keywordtype">float</span> u_disp = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> ((add_point - mls_results_[input_index].mean).dot (mls_results_[input_index].u_axis)),</div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;            v_disp = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> ((add_point - mls_results_[input_index].mean).dot (mls_results_[input_index].v_axis));</div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160; </div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;      PointOutT result_point;</div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;      <a class="code" href="structpcl_1_1_normal.html">pcl::Normal</a> result_normal;</div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;      projectPointToMLSSurface (u_disp, v_disp,</div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;                                mls_results_[input_index].u_axis, mls_results_[input_index].v_axis,</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;                                mls_results_[input_index].plane_normal,</div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;                                mls_results_[input_index].mean,</div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;                                mls_results_[input_index].curvature,</div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;                                mls_results_[input_index].c_vec,</div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;                                mls_results_[input_index].num_neighbors,</div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;                                result_point, result_normal);</div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160; </div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;      <span class="comment">// Copy additional point information if available</span></div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160;      copyMissingFields (input_-&gt;points[input_index], result_point);</div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160; </div>
<div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;      <span class="comment">// Store the id of the original point</span></div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;      corresponding_input_indices_-&gt;indices.push_back (input_index);</div>
<div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160; </div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;      output.<a class="code" href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">push_back</a> (result_point);</div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160; </div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;      <span class="keywordflow">if</span> (compute_normals_)</div>
<div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;        normals_-&gt;push_back (result_normal);</div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;    }</div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;  }</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;}</div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160; </div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt;</div>
<div class="line"><a name="l00700"></a><span class="lineno">  700</span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::MLSResult::MLSResult</a> (<span class="keyword">const</span> Eigen::Vector3d &amp;a_mean,</div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;                                                                    <span class="keyword">const</span> Eigen::Vector3d &amp;a_plane_normal,</div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;                                                                    <span class="keyword">const</span> Eigen::Vector3d &amp;a_u,</div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;                                                                    <span class="keyword">const</span> Eigen::Vector3d &amp;a_v,</div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;                                                                    <span class="keyword">const</span> Eigen::VectorXd a_c_vec,</div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;                                                                    <span class="keyword">const</span> <span class="keywordtype">int</span> a_num_neighbors,</div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;                                                                    <span class="keyword">const</span> <span class="keywordtype">float</span> &amp;a_curvature) :</div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;  mean (a_mean), plane_normal (a_plane_normal), u_axis (a_u), v_axis (a_v), c_vec (a_c_vec), num_neighbors (a_num_neighbors),</div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;  curvature (a_curvature), valid (true)</div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;{</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;}</div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160; </div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt;</div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::MLSVoxelGrid::MLSVoxelGrid</a> (PointCloudInConstPtr&amp; cloud,</div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;    IndicesPtr &amp;indices,</div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;    <span class="keywordtype">float</span> voxel_size) :</div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;    voxel_grid_ (), bounding_min_ (), bounding_max_ (), data_size_ (), voxel_size_ (voxel_size)</div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;{</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;  <a class="code" href="group__common.html#ga3166f09aafd659f69dc75e63f5e10f81">pcl::getMinMax3D</a> (*cloud, *indices, bounding_min_, bounding_max_);</div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160; </div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;  Eigen::Vector4f bounding_box_size = bounding_max_ - bounding_min_;</div>
<div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160;  <span class="keywordtype">double</span> max_size = (std::max) ((std::max)(bounding_box_size.x (), bounding_box_size.y ()), bounding_box_size.z ());</div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;  <span class="comment">// Put initial cloud in voxel grid</span></div>
<div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;  data_size_ = <span class="keyword">static_cast&lt;</span>uint64_t<span class="keyword">&gt;</span> (1.5 * max_size / <a class="code" href="classpcl_1_1_moving_least_squares.html#afbde287f8eb3329c22d0246db630ad58">voxel_size_</a>);</div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; indices-&gt;size (); ++i)</div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;    <span class="keywordflow">if</span> (pcl_isfinite (cloud-&gt;points[(*indices)[i]].x))</div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;    {</div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;      Eigen::Vector3i pos;</div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;      getCellIndex (cloud-&gt;points[(*indices)[i]].getVector3fMap (), pos);</div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160; </div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;      uint64_t index_1d;</div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;      getIndexIn1D (pos, index_1d);</div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;      Leaf leaf;</div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;      voxel_grid_[index_1d] = leaf;</div>
<div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;    }</div>
<div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;}</div>
<div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160; </div>
<div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::MLSVoxelGrid::dilate</a> ()</div>
<div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160;{</div>
<div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;  HashMap new_voxel_grid = voxel_grid_;</div>
<div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;  <span class="keywordflow">for</span> (<span class="keyword">typename</span> MLSVoxelGrid::HashMap::iterator m_it = voxel_grid_.begin (); m_it != voxel_grid_.end (); ++m_it)</div>
<div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;  {</div>
<div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;    Eigen::Vector3i index;</div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;    getIndexIn3D (m_it-&gt;first, index);</div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160; </div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;    <span class="comment">// Now dilate all of its voxels</span></div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> x = -1; x &lt;= 1; ++x)</div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> y = -1; y &lt;= 1; ++y)</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> z = -1; z &lt;= 1; ++z)</div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;          <span class="keywordflow">if</span> (x != 0 || y != 0 || z != 0)</div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;          {</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;            Eigen::Vector3i new_index;</div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;            new_index = index + Eigen::Vector3i (x, y, z);</div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160; </div>
<div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;            uint64_t index_1d;</div>
<div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;            getIndexIn1D (new_index, index_1d);</div>
<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;            Leaf leaf;</div>
<div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;            new_voxel_grid[index_1d] = leaf;</div>
<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;          }</div>
<div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;  }</div>
<div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;  voxel_grid_ = new_voxel_grid;</div>
<div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;}</div>
<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160; </div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160; </div>
<div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>OutT&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;<a class="code" href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares&lt;PointInT, PointOutT&gt;::copyMissingFields</a> (<span class="keyword">const</span> PointInT &amp;point_in,</div>
<div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;                                                                 PointOutT &amp;point_out)<span class="keyword"> const</span></div>
<div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;  PointOutT temp = point_out;</div>
<div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;  <a class="code" href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">copyPoint</a> (point_in, point_out);</div>
<div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160;  point_out.x = temp.x;</div>
<div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;  point_out.y = temp.y;</div>
<div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;  point_out.z = temp.z;</div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;}</div>
<div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160; </div>
<div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160; </div>
<div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;<span class="preprocessor">#define PCL_INSTANTIATE_MovingLeastSquares(T,OutT) template class PCL_EXPORTS pcl::MovingLeastSquares&lt;T,OutT&gt;;</span></div>
<div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160; </div>
<div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;<span class="preprocessor">#define PCL_INSTANTIATE_MovingLeastSquaresOMP(T,OutT) template class PCL_EXPORTS pcl::MovingLeastSquaresOMP&lt;T,OutT&gt;;</span></div>
<div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160; </div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;<span class="preprocessor">#endif    </span><span class="comment">// PCL_SURFACE_IMPL_MLS_H_</span></div>
<div class="ttc" id="acentroid_8h_html"><div class="ttname"><a href="centroid_8h.html">centroid.h</a></div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_1_1_m_l_s_voxel_grid_html"><div class="ttname"><a href="classpcl_1_1_moving_least_squares_1_1_m_l_s_voxel_grid.html">pcl::MovingLeastSquares::MLSVoxelGrid</a></div><div class="ttdoc">A minimalistic implementation of a voxel grid, necessary for the point cloud upsampling</div><div class="ttdef"><b>Definition:</b> mls.h:377</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares</a></div><div class="ttdoc">MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data s...</div><div class="ttdef"><b>Definition:</b> mls.h:66</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_a0e2f25248f7f01a111763877698e06e4"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#a0e2f25248f7f01a111763877698e06e4">pcl::MovingLeastSquares::projectPointToMLSSurface</a></div><div class="ttdeci">void projectPointToMLSSurface(float &amp;u_disp, float &amp;v_disp, Eigen::Vector3d &amp;u_axis, Eigen::Vector3d &amp;v_axis, Eigen::Vector3d &amp;n_axis, Eigen::Vector3d &amp;mean, float &amp;curvature, Eigen::VectorXd &amp;c_vec, int num_neighbors, PointOutT &amp;result_point, pcl::Normal &amp;result_normal) const</div><div class="ttdoc">Fits a point (sample point) given in the local plane coordinates of an input point (query point) to t...</div><div class="ttdef"><b>Definition:</b> mls.hpp:409</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_a1a4ffe40c701474aa4f18758d2432ca7"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#a1a4ffe40c701474aa4f18758d2432ca7">pcl::MovingLeastSquares::performUpsampling</a></div><div class="ttdeci">void performUpsampling(PointCloudOut &amp;output)</div><div class="ttdoc">Perform upsampling for the distinct-cloud and voxel-grid methods</div><div class="ttdef"><b>Definition:</b> mls.hpp:590</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ad168be16626ea58d1c31c321bd1d980f"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ad168be16626ea58d1c31c321bd1d980f">pcl::MovingLeastSquares::process</a></div><div class="ttdeci">void process(PointCloudOut &amp;output)</div><div class="ttdoc">Base method for surface reconstruction for all points given in &lt;setInputCloud (), setIndices ()&gt;</div><div class="ttdef"><b>Definition:</b> mls.hpp:57</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ae27440d95b1fc5568b2ec820302654a4"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ae27440d95b1fc5568b2ec820302654a4">pcl::MovingLeastSquares::performProcessing</a></div><div class="ttdeci">virtual void performProcessing(PointCloudOut &amp;output)</div><div class="ttdoc">Abstract surface reconstruction method.</div><div class="ttdef"><b>Definition:</b> mls.hpp:466</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_af89da1f47e32a533e5c0c75d1a244a74"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#af89da1f47e32a533e5c0c75d1a244a74">pcl::MovingLeastSquares::computeMLSPointNormal</a></div><div class="ttdeci">void computeMLSPointNormal(int index, const std::vector&lt; int &gt; &amp;nn_indices, std::vector&lt; float &gt; &amp;nn_sqr_dists, PointCloudOut &amp;projected_points, NormalCloud &amp;projected_points_normals, PointIndices &amp;corresponding_input_indices, MLSResult &amp;mls_result) const</div><div class="ttdoc">Smooth a given point and its neighborghood using Moving Least Squares.</div><div class="ttdef"><b>Definition:</b> mls.hpp:165</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_afbde287f8eb3329c22d0246db630ad58"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#afbde287f8eb3329c22d0246db630ad58">pcl::MovingLeastSquares::voxel_size_</a></div><div class="ttdeci">float voxel_size_</div><div class="ttdoc">Voxel size for the VOXEL_GRID_DILATION upsampling method</div><div class="ttdef"><b>Definition:</b> mls.h:430</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a></div><div class="ttdoc">PointCloud represents the base class in PCL for storing collections of 3D points.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:173</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a0b4d7abee110e47d90635eb042488bb4"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a0b4d7abee110e47d90635eb042488bb4">pcl::PointCloud::push_back</a></div><div class="ttdeci">void push_back(const PointT &amp;pt)</div><div class="ttdoc">Insert a new point in the cloud, at the end of the container.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:480</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a2185a6453f8ad905d7bdf7b45754a160"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">pcl::PointCloud::width</a></div><div class="ttdeci">uint32_t width</div><div class="ttdoc">The point cloud width (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:413</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a4f34b45220c57f96607513ffad0d9582"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">pcl::PointCloud::height</a></div><div class="ttdeci">uint32_t height</div><div class="ttdoc">The point cloud height (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:415</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a75387c07a2d24ee943eb71ab1c00e4a7"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a75387c07a2d24ee943eb71ab1c00e4a7">pcl::PointCloud::insert</a></div><div class="ttdeci">iterator insert(iterator position, const PointT &amp;pt)</div><div class="ttdoc">Insert a new point in the cloud, given an iterator.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:494</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a82e0be055a617e5e74102ed62712b352"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">pcl::PointCloud::header</a></div><div class="ttdeci">pcl::PCLHeader header</div><div class="ttdoc">The point cloud header. It contains information about the acquisition time.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:407</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a></div><div class="ttdoc">search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...</div><div class="ttdef"><b>Definition:</b> kdtree.h:63</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_organized_neighbor_html"><div class="ttname"><a href="classpcl_1_1search_1_1_organized_neighbor.html">pcl::search::OrganizedNeighbor</a></div><div class="ttdoc">OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds.</div><div class="ttdef"><b>Definition:</b> organized.h:63</div></div>
<div class="ttc" id="acommon_2include_2pcl_2common_2geometry_8h_html"><div class="ttname"><a href="common_2include_2pcl_2common_2geometry_8h.html">geometry.h</a></div></div>
<div class="ttc" id="agroup__common_html_ga3166f09aafd659f69dc75e63f5e10f81"><div class="ttname"><a href="group__common.html#ga3166f09aafd659f69dc75e63f5e10f81">pcl::getMinMax3D</a></div><div class="ttdeci">void getMinMax3D(const pcl::PointCloud&lt; PointT &gt; &amp;cloud, PointT &amp;min_pt, PointT &amp;max_pt)</div><div class="ttdoc">Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud</div><div class="ttdef"><b>Definition:</b> common.hpp:228</div></div>
<div class="ttc" id="agroup__common_html_gab978bf1754771246b2f140a5b52a8f8b"><div class="ttname"><a href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">pcl::copyPoint</a></div><div class="ttdeci">void copyPoint(const PointInT &amp;point_in, PointOutT &amp;point_out)</div><div class="ttdoc">Copy the fields of a source point into a target point.</div><div class="ttdef"><b>Definition:</b> copy_point.hpp:138</div></div>
<div class="ttc" id="agroup__common_html_gac36b146ec26b1ceb7be43a9ecaa010c4"><div class="ttname"><a href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">pcl::computeCovarianceMatrix</a></div><div class="ttdeci">unsigned int computeCovarianceMatrix(const pcl::PointCloud&lt; PointT &gt; &amp;cloud, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</div><div class="ttdoc">Compute the 3x3 covariance matrix of a given set of points. The result is returned as a Eigen::Matrix...</div></div>
<div class="ttc" id="agroup__common_html_gaca873868052e7d26efcf4b684a17bef2"><div class="ttname"><a href="group__common.html#gaca873868052e7d26efcf4b684a17bef2">pcl::eigen33</a></div><div class="ttdeci">void eigen33(const Matrix &amp;mat, typename Matrix::Scalar &amp;eigenvalue, Vector &amp;eigenvector)</div><div class="ttdoc">determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi d...</div><div class="ttdef"><b>Definition:</b> eigen.hpp:251</div></div>
<div class="ttc" id="agroup__common_html_gaf5729fae15603888b49743b118025290"><div class="ttname"><a href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a></div><div class="ttdeci">unsigned int compute3DCentroid(ConstCloudIterator&lt; PointT &gt; &amp;cloud_iterator, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</div><div class="ttdoc">Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.</div><div class="ttdef"><b>Definition:</b> centroid.hpp:50</div></div>
<div class="ttc" id="astructpcl_1_1_moving_least_squares_1_1_m_l_s_result_html"><div class="ttname"><a href="structpcl_1_1_moving_least_squares_1_1_m_l_s_result.html">pcl::MovingLeastSquares::MLSResult</a></div><div class="ttdoc">Data structure used to store the results of the MLS fitting</div><div class="ttdef"><b>Definition:</b> mls.h:349</div></div>
<div class="ttc" id="astructpcl_1_1_normal_html"><div class="ttname"><a href="structpcl_1_1_normal.html">pcl::Normal</a></div><div class="ttdoc">A point structure representing normal coordinates and the surface curvature estimate....</div><div class="ttdef"><b>Definition:</b> point_types.hpp:779</div></div>
<div class="ttc" id="astructpcl_1_1_point_indices_html"><div class="ttname"><a href="structpcl_1_1_point_indices.html">pcl::PointIndices</a></div><div class="ttdef"><b>Definition:</b> PointIndices.h:13</div></div>
<div class="ttc" id="astructpcl_1_1_set_if_field_exists_html"><div class="ttname"><a href="structpcl_1_1_set_if_field_exists.html">pcl::SetIfFieldExists</a></div><div class="ttdoc">A helper functor that can set a specific value in a field if the field exists.</div><div class="ttdef"><b>Definition:</b> point_traits.h:292</div></div>
<div class="ttc" id="astructpcl_1_1traits_1_1field_list_html"><div class="ttname"><a href="structpcl_1_1traits_1_1field_list.html">pcl::traits::fieldList</a></div><div class="ttdef"><b>Definition:</b> point_traits.h:177</div></div>
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